Share the Insight

In [2]:

    

# Import the library we need, which is dplyr and ggplot2
library(dplyr)
library(ggplot2)


    

In [3]:

    

# Read the csv file of Monthwise Quantity and Price csv file we have.
df <- read.csv('MonthWiseMarketArrivals_Clean.csv')


    

In [4]:

    

str(df)


    

    




'data.frame':	10320 obs. of  10 variables:
 $ market  : Factor w/ 122 levels "ABOHAR(PB)","AGRA(UP)",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ month   : Factor w/ 12 levels "April","August",..: 5 5 5 5 5 5 5 5 4 4 ...
 $ year    : int  2005 2006 2010 2011 2012 2013 2014 2015 2005 2006 ...
 $ quantity: int  2350 900 790 245 1035 675 440 1305 1400 1800 ...
 $ priceMin: int  404 487 1283 3067 523 1327 1025 1309 286 343 ...
 $ priceMax: int  493 638 1592 3750 686 1900 1481 1858 365 411 ...
 $ priceMod: int  446 563 1460 3433 605 1605 1256 1613 324 380 ...
 $ city    : Factor w/ 119 levels "ABOHAR","AGRA",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ state   : Factor w/ 22 levels "AP","ASM","BHR",..: 17 17 17 17 17 17 17 17 17 17 ...
 $ date    : Factor w/ 243 levels "1996-01-01","1996-02-01",..: 109 121 169 181 193 205 217 229 110 122 ...

In [5]:

    

# Fix the date
df$date = as.Date(as.character(df$date), "%Y-%m-%d")


    

In [6]:

    

# Get the data for year 2015 and sort
df2015City <- df %>% 
          filter(year == 2015) %>%
          group_by(city) %>%
          summarize(quantity_year = sum(quantity)) %>%
          arrange(desc(quantity_year))


    

In [7]:

    

head(df2015City)


    

    
Out[7]:





city
quantity_year

	
1
BANGALORE
8267060
	
2
MAHUVA
5113510
	
3
SOLAPUR
4162041
	
4
PUNE
3591209
	
5
LASALGAON
3581359
	
6
PIMPALGAON
3455265

In [8]:

    

df2015City$city <- as.character(df2015City$city)
str(df2015City)


    

    




Classes 'tbl_df', 'tbl' and 'data.frame':	111 obs. of  2 variables:
 $ city         : chr  "BANGALORE" "MAHUVA" "SOLAPUR" "PUNE" ...
 $ quantity_year: int  8267060 5113510 4162041 3591209 3581359 3455265 3272139 2971205 2444020 1882161 ...

In [ ]:

    

install.packages('ggmap',repos="http://ftp.iitm.ac.in/cran")


    

In [9]:

    

library(ggmap)


    

In [10]:

    

geocode('Bangalore')


    

    




Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Bangalore&sensor=false






    
Out[10]:





lon
lat

	
1
77.59456
12.9716

In [11]:

    

# Let us get the city, state name strings to run through this
dfGeo <- df %>%
         mutate(city_state = paste(city, state, sep=", ")) %>%
         select(city, state, city_state) %>%
         distinct(city_state)


    

In [13]:

    

head(dfGeo)


    

    
Out[13]:





city
state
city_state

	
1
ABOHAR
PB
ABOHAR, PB
	
2
AGRA
UP
AGRA, UP
	
3
AHMEDABAD
GUJ
AHMEDABAD, GUJ
	
4
AHMEDNAGAR
MS
AHMEDNAGAR, MS
	
5
AJMER
RAJ
AJMER, RAJ
	
6
ALIGARH
UP
ALIGARH, UP

In [12]:

    

str(dfGeo)


    

    




'data.frame':	119 obs. of  3 variables:
 $ city      : Factor w/ 119 levels "ABOHAR","AGRA",..: 1 2 3 4 5 6 7 8 9 10 ...
 $ state     : Factor w/ 22 levels "AP","ASM","BHR",..: 17 21 5 15 18 21 18 17 21 12 ...
 $ city_state: chr  "ABOHAR, PB" "AGRA, UP" "AHMEDABAD, GUJ" "AHMEDNAGAR, MS" ...

In [14]:

    

dfGeo$city <- as.character(dfGeo$city)


    

In [15]:

    

dim(dfGeo)


    

    
Out[15]:





	
119
	
3

In [16]:

    

dfGeo$city


    

    
Out[16]:





	
'ABOHAR'
	
'AGRA'
	
'AHMEDABAD'
	
'AHMEDNAGAR'
	
'AJMER'
	
'ALIGARH'
	
'ALWAR'
	
'AMRITSAR'
	
'BALLIA'
	
'BANGALORE'
	
'BAREILLY'
	
'BELGAUM'
	
'BHATINDA'
	
'BHAVNAGAR'
	
'BHOPAL'
	
'BHUBNESWER'
	
'BIHARSHARIF'
	
'BIJAPUR'
	
'BIKANER'
	
'BOMBORI'
	
'BURDWAN'
	
'CHAKAN'
	
'CHALLAKERE'
	
'CHANDIGARH'
	
'CHANDVAD'
	
'CHENNAI'
	
'CHICKBALLAPUR'
	
'COIMBATORE'
	
'DEESA'
	
'DEHRADOON'
	
'DELHI'
	
'DEORIA'
	
'DEVALA'
	
'DEWAS'
	
'DHAVANGERE'
	
'DHULIA'
	
'DINDIGUL'
	
'DINDORI'
	
'ETAWAH'
	
'FARUKHABAD'
	
'GONDAL'
	
'GORAKHPUR'
	
'GUWAHATI'
	
'HALDWANI'
	
'HASSAN'
	
'HOSHIARPUR'
	
'HUBLI'
	
'HYDERABAD'
	
'INDORE'
	
'JAIPUR'
	
'JALANDHAR'
	
'JALGAON'
	
'JAMMU'
	
'JAMNAGAR'
	
'JHANSI'
	
'JODHPUR'
	
'JUNNAR'
	
'KALVAN'
	
'KANPUR'
	
'KARNAL'
	
'KHANNA'
	
'KOLAR'
	
'KOLHAPUR'
	
'KOLKATA'
	
'KOPERGAON'
	
'KOTA'
	
'KURNOOL'
	
'LASALGAON'
	
'LONAND'
	
'LUCKNOW'
	
'LUDHIANA'
	
'MADURAI'
	
'MAHUVA'
	
'MALEGAON'
	
'MANDSOUR'
	
'MANMAD'
	
'MEERUT'
	
'MIDNAPUR'
	
'MUMBAI'
	
'NAGPUR'
	
'NANDGAON'
	
'NASIK'
	
'NEEMUCH'
	
'NEWASA'
	
'NIPHAD'
	
'PALAYAM'
	
'PATIALA'
	
'PATNA'
	
'PHALTAN '
	
'PIMPALGAON'
	
'PUNE'
	
'PURULIA'
	
'RAHATA'
	
'RAHURI'
	
'RAICHUR'
	
'RAIPUR'
	
'RAJAHMUNDRY'
	
'RAJKOT'
	
'RANCHI'
	
'SAGAR'
	
'SAIKHEDA'
	
'SANGALI'
	
'SANGAMNER'
	
'SATANA'
	
'SHEROAPHULY'
	
'SHIMLA'
	
'SHRIRAMPUR'
	
'SINNAR'
	
'SOLAPUR'
	
'SRIGANGANAGAR'
	
'SRINAGAR'
	
'SRIRAMPUR'
	
'SURAT'
	
'TRIVENDRUM'
	
'UDAIPUR'
	
'UJJAIN'
	
'VANI'
	
'VARANASI'
	
'YEOLA'

In [17]:

    

geos <- geocode(dfGeo$city)


    

    




Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=ABOHAR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=AGRA&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=AHMEDABAD&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=AHMEDNAGAR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=AJMER&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=ALIGARH&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=ALWAR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=AMRITSAR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BALLIA&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BANGALORE&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BAREILLY&sensor=false
Warning message:
In readLines(connect, warn = FALSE): unable to connect to 'maps.googleapis.com' on port 80.Warning message:
In FUN(X[[i]], ...):   geocoding failed for "BAREILLY".
  if accompanied by 500 Internal Server Error with using dsk, try google.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BELGAUM&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BHATINDA&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BHAVNAGAR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BHOPAL&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BHUBNESWER&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BIHARSHARIF&sensor=false
Warning message:
: geocode failed with status OVER_QUERY_LIMIT, location = "BIHARSHARIF"Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BIJAPUR&sensor=false
Warning message:
: geocode failed with status OVER_QUERY_LIMIT, location = "BIJAPUR"Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BIKANER&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BOMBORI&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=BURDWAN&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=CHAKAN&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=CHALLAKERE&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=CHANDIGARH&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=CHANDVAD&sensor=false
Warning message:
: geocode failed with status OVER_QUERY_LIMIT, location = "CHANDVAD".Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=CHENNAI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=CHICKBALLAPUR&sensor=false
Warning message:
: geocode failed with status OVER_QUERY_LIMIT, location = "CHICKBALLAPUR"Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=COIMBATORE&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DEESA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DEHRADOON&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DELHI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DEORIA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DEVALA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DEWAS&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DHAVANGERE&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DHULIA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DINDIGUL&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=DINDORI&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=ETAWAH&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=FARUKHABAD&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=GONDAL&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=GORAKHPUR&sensor=false
Warning message:
: geocode failed with status OVER_QUERY_LIMIT, location = "GORAKHPUR"Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=GUWAHATI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=HALDWANI&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=HASSAN&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=HOSHIARPUR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=HUBLI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=HYDERABAD&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=INDORE&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=JAIPUR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=JALANDHAR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=JALGAON&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=JAMMU&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=JAMNAGAR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=JHANSI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=JODHPUR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=JUNNAR&sensor=false
Warning message:
: geocode failed with status OVER_QUERY_LIMIT, location = "JUNNAR".Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KALVAN&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KANPUR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KARNAL&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KHANNA&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KOLAR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KOLHAPUR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KOLKATA&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KOPERGAON&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KOTA&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=KURNOOL&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=LASALGAON&sensor=false
Warning message:
: geocode failed with status OVER_QUERY_LIMIT, location = "LASALGAON".Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=LONAND&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=LUCKNOW&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=LUDHIANA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=MADURAI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=MAHUVA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=MALEGAON&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=MANDSOUR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=MANMAD&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=MEERUT&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=MIDNAPUR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=MUMBAI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=NAGPUR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=NANDGAON&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=NASIK&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=NEEMUCH&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=NEWASA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=NIPHAD&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=PALAYAM&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=PATIALA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=PATNA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=PHALTAN%20&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=PIMPALGAON&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=PUNE&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=PURULIA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=RAHATA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=RAHURI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=RAICHUR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=RAIPUR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=RAJAHMUNDRY&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=RAJKOT&sensor=false
Warning message:
: geocode failed with status OVER_QUERY_LIMIT, location = "RAJKOT".Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=RANCHI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SAGAR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SAIKHEDA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SANGALI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SANGAMNER&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SATANA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SHEROAPHULY&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SHIMLA&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SHRIRAMPUR&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SINNAR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SOLAPUR&sensor=false
Warning message:
: geocode failed with status OVER_QUERY_LIMIT, location = "SOLAPUR".Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SRIGANGANAGAR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SRINAGAR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SRIRAMPUR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=SURAT&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=TRIVENDRUM&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=UDAIPUR&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=UJJAIN&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=VANI&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=VARANASI&sensor=false
.Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=YEOLA&sensor=false

In [18]:

    

head(geos)


    

    
Out[18]:





lon
lat

	
1
74.1993
30.14529
	
2
78.00807
27.17667
	
3
72.57136
23.0225
	
4
74.74959
19.09521
	
5
74.63992
26.4499
	
6
78.08801
27.89739

In [19]:

    

dfGeo <- bind_cols(dfGeo, geos)


    

In [20]:

    

head(dfGeo)


    

    
Out[20]:





city
state
city_state
lon
lat

	
1
ABOHAR
PB
ABOHAR, PB
74.1993
30.14529
	
2
AGRA
UP
AGRA, UP
78.00807
27.17667
	
3
AHMEDABAD
GUJ
AHMEDABAD, GUJ
72.57136
23.0225
	
4
AHMEDNAGAR
MS
AHMEDNAGAR, MS
74.74959
19.09521
	
5
AJMER
RAJ
AJMER, RAJ
74.63992
26.4499
	
6
ALIGARH
UP
ALIGARH, UP
78.08801
27.89739

In [21]:

    

# Check for consitency
ggplot(dfGeo) + aes(lon, lat) + geom_point()


    

    




Warning message:
: Removed 10 rows containing missing values (geom_point).





    

In [22]:

    

# Check for consistency
dfGeo %>% filter(lon <65)


    

    
Out[22]:





city
state
city_state
lon
lat

	
1
BOMBORI
MS
BOMBORI, MS
10.42254
12.87311
	
2
KALVAN
MS
KALVAN, MS
49.35262
34.65133
	
3
VANI
MS
VANI, MS
43.37298
38.50121

In [23]:

    

# Imputing the values of 
newGeo <- geocode(c("Bombay, Maharashtra", "Kalyan", "Vani,Maharashtra"))


    

    




Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Bombay,%20Maharashtra&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Kalyan&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Vani,Maharashtra&sensor=false

In [24]:

    

newGeo


    

    
Out[24]:





lon
lat

	
1
72.87766
19.07598
	
2
73.13054
19.24033
	
3
73.89189
20.33749

In [25]:

    

dfGeo$lat[dfGeo$city == "BOMBORI"] <- newGeo$lat[1]
dfGeo$lon[dfGeo$city == "BOMBORI"] <- newGeo$lon[1]


    

In [26]:

    

dfGeo$lat[dfGeo$city == "KALVAN"] <- newGeo$lat[2]
dfGeo$lon[dfGeo$city == "KALVAN"] <- newGeo$lon[2]


    

In [27]:

    

dfGeo$lat[dfGeo$city == "VANI"] <- newGeo$lat[3]
dfGeo$lon[dfGeo$city == "VANI"] <- newGeo$lon[3]


    

In [28]:

    

# Check for consistency
dfGeo %>% filter(lon <65)


    

    
Out[28]:





city
state
city_state
lon
lat

In [29]:

    

# Check for consitency
ggplot(dfGeo) + aes(lon, lat) + geom_point()


    

    




Warning message:
: Removed 10 rows containing missing values (geom_point).





    

In [38]:

    

is.vector(is.na(dfGeo$lon))


    

    
Out[38]:




TRUE

In [39]:

    

dfGeo[is.na(dfGeo$lon),]


    

    
Out[39]:





city
state
city_state
lon
lat

	
1
BAREILLY
UP
BAREILLY, UP
NA
NA
	
2
BIHARSHARIF
BHR
BIHARSHARIF, BHR
NA
NA
	
3
BIJAPUR
KNT
BIJAPUR, KNT
NA
NA
	
4
CHANDVAD
MS
CHANDVAD, MS
NA
NA
	
5
CHICKBALLAPUR
KNT
CHICKBALLAPUR, KNT
NA
NA
	
6
GORAKHPUR
UP
GORAKHPUR, UP
NA
NA
	
7
JUNNAR
MS
JUNNAR, MS
NA
NA
	
8
LASALGAON
MS
LASALGAON, MS
NA
NA
	
9
RAJKOT
GUJ
RAJKOT, GUJ
NA
NA
	
10
SOLAPUR
MS
SOLAPUR, MS
NA
NA

In [41]:

    

df2015CityGeo = left_join(df2015City, dfGeo, by='city')


    

In [42]:

    

head(df2015CityGeo)


    

    
Out[42]:





city
quantity_year
state
city_state
lon
lat

	
1
BANGALORE
8267060
KNT
BANGALORE, KNT
77.59456
12.9716
	
2
MAHUVA
5113510
GUJ
MAHUVA, GUJ
71.75632
21.09022
	
3
SOLAPUR
4162041
MS
SOLAPUR, MS
NA
NA
	
4
PUNE
3591209
MS
PUNE, MS
73.85674
18.52043
	
5
LASALGAON
3581359
MS
LASALGAON, MS
NA
NA
	
6
PIMPALGAON
3455265
MS
PIMPALGAON, MS
73.98738
20.16997

In [43]:

    

str(df2015CityGeo)


    

    




Classes 'tbl_df', 'tbl' and 'data.frame':	111 obs. of  6 variables:
 $ city         : chr  "BANGALORE" "MAHUVA" "SOLAPUR" "PUNE" ...
 $ quantity_year: int  8267060 5113510 4162041 3591209 3581359 3455265 3272139 2971205 2444020 1882161 ...
 $ state        : Factor w/ 22 levels "AP","ASM","BHR",..: 12 5 15 15 15 15 4 13 15 14 ...
 $ city_state   : chr  "BANGALORE, KNT" "MAHUVA, GUJ" "SOLAPUR, MS" "PUNE, MS" ...
 $ lon          : num  77.6 71.8 NA 73.9 NA ...
 $ lat          : num  13 21.1 NA 18.5 NA ...

In [44]:

    

ggplot(df2015CityGeo) + aes(lon, lat) + geom_point()


    

    




Warning message:
: Removed 9 rows containing missing values (geom_point).





    

In [45]:

    

ggplot(df2015CityGeo) + aes(lon, lat) + geom_point() + coord_map()


    

    




Warning message:
: Removed 9 rows containing missing values (geom_point).





    

In [57]:

    

ggplot(df2015CityGeo) + aes(lon, lat, size = quantity_year) + geom_point(alpha = 0.5) + coord_map() + 
  scale_size_continuous(range=c(0,20))


    

    




Warning message:
: Removed 9 rows containing missing values (geom_point).





    

In [79]:

    

ggplot(df2015CityGeo) + aes(lon, lat, size = quantity_year/1000, colour = state) + geom_point(alpha = 0.5) + coord_map() + scale_size_continuous(range=c(0,20))


    

    




Warning message:
: Incompatible methods ("+.gg", "Ops.data.frame") for "+"





    




Error in p + o: non-numeric argument to binary operator

In [48]:

    

dfState <- read.csv('state_geocode.csv')


    

In [49]:

    

head(dfState)


    

    
Out[49]:





state
name
lon
lat

	
1
MS
Maharashtra
75.71389
19.75148
	
2
GUJ
Gujarat
71.19238
22.25865
	
3
MP
Madhya pradesh
78.65689
22.97342
	
4
TN
Tamil Nadu
78.65689
11.12712
	
5
KNT
Karnataka
75.71389
15.31728
	
6
DEL
Delhi
77.20902
28.61394

In [68]:

    

map <- get_map("India", zoom = 5)


    

    




Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=India&zoom=5&size=640x640&scale=2&maptype=terrain&language=en-EN&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=India&sensor=false

In [69]:

    

ggmap(map)


    

In [87]:

    

map1 <- get_map("India", maptype = "watercolor", source = "stamen", zoom = 5)


    

    




Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=India&zoom=5&size=640x640&scale=2&maptype=terrain&sensor=false
Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=India&sensor=false
Map from URL : http://tile.stamen.com/watercolor/5/21/12.jpg
Map from URL : http://tile.stamen.com/watercolor/5/22/12.jpg
Map from URL : http://tile.stamen.com/watercolor/5/23/12.jpg
Map from URL : http://tile.stamen.com/watercolor/5/24/12.jpg
Map from URL : http://tile.stamen.com/watercolor/5/21/13.jpg
Map from URL : http://tile.stamen.com/watercolor/5/22/13.jpg
Map from URL : http://tile.stamen.com/watercolor/5/23/13.jpg
Map from URL : http://tile.stamen.com/watercolor/5/24/13.jpg
Map from URL : http://tile.stamen.com/watercolor/5/21/14.jpg
Map from URL : http://tile.stamen.com/watercolor/5/22/14.jpg
Map from URL : http://tile.stamen.com/watercolor/5/23/14.jpg
Map from URL : http://tile.stamen.com/watercolor/5/24/14.jpg
Map from URL : http://tile.stamen.com/watercolor/5/21/15.jpg
Map from URL : http://tile.stamen.com/watercolor/5/22/15.jpg
Map from URL : http://tile.stamen.com/watercolor/5/23/15.jpg
Map from URL : http://tile.stamen.com/watercolor/5/24/15.jpg

In [88]:

    

ggmap(map1)


    

In [90]:

    

ggmap(map1) + geom_point(data = df2015CityGeo,aes(lon,lat,size=quantity_year/1000,color=state))


    

    




Warning message:
: Removed 10 rows containing missing values (geom_point).





    

In [ ]: