My goal is to (1) import Twitter JSON, (2) extract data of interest, (3) create pandas data frame for the variables of interest. Here is my code:
import json
import pandas as pd
tweets = []
for line in open('00.json'):
try:
tweet = json.loads(line)
tweets.append(tweet)
except:
continue
# Tweets often have missing data, therefore use -if- when extracting "keys"
tweet = tweets[0]
ids = [tweet['id_str'] for tweet in tweets if 'id_str' in tweet]
text = [tweet['text'] for tweet in tweets if 'text' in tweet]
lang = [tweet['lang'] for tweet in tweets if 'lang' in tweet]
geo = [tweet['geo'] for tweet in tweets if 'geo' in tweet]
place = [tweet['place'] for tweet in tweets if 'place' in tweet]
# Create a data frame (using pd.Index may be "incorrect", but I am a noob)
df=pd.DataFrame({'Ids':pd.Index(ids),
'Text':pd.Index(text),
'Lang':pd.Index(lang),
'Geo':pd.Index(geo),
'Place':pd.Index(place)})
# Create a data frame satisfying conditions:
df2 = df[(df['Lang']==('en')) & (df['Geo'].dropna())]
So far, everything seems to be working fine.
Now, the extracted values for Geo result in the following example:
df2.loc[1921,'Geo']
{'coordinates': [39.11890951, -84.48903638], 'type': 'Point'}
To get rid of everything except the coordinates inside the squared brackets I tried using:
df2.Geo.str.replace("[({':]", "") ### results in NaN
# and also this:
df2['Geo'] = df2['Geo'].map(lambda x: x.lstrip('{'coordinates': [').rstrip('], 'type': 'Point'')) ### results in syntax error
Please advise on the correct way to obtain coordinates values only.
The following line from your question indicates that this is an issue with understanding the underlying data type of the returned object.
df2.loc[1921,'Geo']
{'coordinates': [39.11890951, -84.48903638], 'type': 'Point'}
You are returning a Python dictionary here -- not a string! If you want to return just the values of the coordinates, you should just use the 'coordinates' key to return those values, e.g.
df2.loc[1921,'Geo']['coordinates']
[39.11890951, -84.48903638]
The returned object in this case will be a Python list object containing the two coordinate values. If you want just one of the values, you can slice the list, e.g.
df2.loc[1921,'Geo']['coordinates'][0]
39.11890951
This workflow is much easier to deal with than casting the dictionary to a string, parsing the string, and recapturing the coordinate values as you are trying to do.
So let's say you want to create a new column called "geo_coord0" which contains all of the coordinates in the first position (as shown above). You could use a something like the following:
df2["geo_coord0"] = [x['coordinates'][0] for x in df2['Geo']]
This uses a Python list comprehension to iterate over all entries in the df2['Geo'] column and for each entry it uses the same syntax we used above to return the first coordinate value. It then assigns these values to a new column in df2.
See the Python documentation on data structures for more details on the data structures discussed above.
Related
I am trying to scrape the pokemon API and create a dataset for all pokemon. So I have written a function which looks like this:
import requests
import json
import pandas as pd
def poke_scrape(x, y):
'''
A function that takes in a range of pokemon (based on pokedex ID) and returns
a pandas dataframe with information related to the pokemon using the Poke API
'''
#GATERING THE DATA FROM API
url = 'https://pokeapi.co/api/v2/pokemon/'
ids = range(x, (y+1))
pkmn = []
for id_ in ids:
url = 'https://pokeapi.co/api/v2/pokemon/' + str(id_)
pages = requests.get(url).json()
# content = json.dumps(pages, indent = 4, sort_keys=True)
if 'error' not in pages:
pkmn.append([pages['id'], pages['name'], pages['abilities'], pages['stats'], pages['types']])
#MAKING A DATAFRAME FROM GATHERED API DATA
cols = ['id', 'name', 'abilities', 'stats', 'types']
df = pd.DataFrame(pkmn, columns=cols)
The code works fine for most pokemon. However, when I am trying to run poke_scrape(229, 229) (so trying to load ONLY the 229th pokemon), it gives me the JSONDecodeError. It looks like this:
So far I have tried using json.loads() instead but that has not solved the issue. What is even more perplexing is that specific pokemon has loaded before and the same issue was with another ID - otherwise I could just manually enter the stats for the specific pokemon that is unable to load into my dataframe. Any help is appreciated!
Because of the way the PokeAPI works, some links to the JSON data for each pokemon only load when the links end with a '/' (such as https://pokeapi.co/api/v2/pokemon/229/ vs https://pokeapi.co/api/v2/pokemon/229 - first link will work and the second will return not found). However, others will respond with a response error because of the added '/' so fixed the issue with a few if statements right after the for loop in the beginning of the function
I'm trying to create a GeoDataFrame with 2 zip codes per row, whose distances from each other I want to compare.
I took a list of approx 220 zip codes and ran an itertools combination on them to get all combo's, then unpacked the tuples into two columns
code_combo = list(itertools.combinations(df_with_all_zip_codes['code'], 2))
df_distance_ctr = pd.DataFrame(code_combo, columns=['first_code','second_code'])
Then I did some standard pandas merges and column renaming to get the polygon/geometry column from the original geodataframe into this new one, right beside the respective zip code columns.
The problem is I can't seem to get the polygon columns to be read as geometry, even after 1.) attempting to convert the dataframe to a geodataframe - AttributeError: No geometry data set yet, 2.) applying wkt.loads to the geometry column - AttributeError: 'MultiPolygon' object has no attribute 'encode'
.
I've tried to look for a way to convert a series to a geoseries but can't find anything on SO nor the documentation. Can anyone please point out where I'm likely going wrong?
Looking at the __init__ method of a GeoDataFrame at https://github.com/geopandas/geopandas/blob/master/geopandas/geodataframe.py, it looks like a GDF can only have one column at a time. The other columns you've created should still have geometry objects in them though.
Since you still have geometry objects in each column, you could write a method that uses Shapely's distance method, like so:
import pandas as pd
import geopandas
from shapely.geometry import Point
import matplotlib.pyplot as plt
lats = [-34.58, -15.78, -33.45, 4.60, 10.48]
lons = [-58.66, -47.91, -70.66, -74.08, -66.86]
df = pd.DataFrame(
{'City': ['Buenos Aires', 'Brasilia', 'Santiago', 'Bogota', 'Caracas'],
'Country': ['Argentina', 'Brazil', 'Chile', 'Colombia', 'Venezuela'],
'Latitude': lats,
'Longitude': lons})
df['Coordinates'] = list(zip(df.Longitude, df.Latitude))
df['Coordinates'] = df['Coordinates'].apply(Point)
df['Coordinates_2'] = list(zip(lons[::-1], lats[::-1]))
df['Coordinates_2'] = df['Coordinates_2'].apply(Point)
gdf = geopandas.GeoDataFrame(df, geometry='Coordinates')
def get_distance(row):
distance = row.Coordinates.distance(row.Coordinates_2)
print(distance)
return distance
gdf['distance'] = gdf.apply(lambda row: get_distance(row), axis=1)
As for the AttributeError: 'MultiPolygon' object has no attribute 'encode'. MultiPolygon is a Shapely geometry class. encode is usually a method on string objects so you can probably remove the call to wkt.loads.
I have Python dict containing 4 key value pairs. Each value is a numpy arrays. Now I want to print the whole dict to a csv, forcing to write one numpy array per row.
with open(os.path.join("csv", title), 'w', newline='') as f:
w = csv.DictWriter(f, list(data.keys()))
w.writeheader()
w.writerow(data)
Is what I have used yet. But some of my arrays get written to several rows instead of a single line.
Here an example of input data:
{'DE': array([[ 38574. , 38538.1904, 39511.6190, 42521.1428,
50586. , 46282.5238, 42714.4761, 40612.0476],
[ 42798.4666, 42112.5333, 42277.8666, 42886.1333,
50224.3333, 48148.8 , 44272.6666, 41210.2 ]])}
I expect the output so that, each line of my array is written on one line. Instead I get a file containing "\n" after a certain amount of digits. how can i force to write the whole array in one row?
DE has a multidimensional array as its value, Inter has an empty list as its value, you end up with two columns one with Inter as the header with an empty list in its column and a second column DE with the array in its column which is exactly what the code should be doing.
If you want to alter each array length try setting numpy.set_printoptions:
numpy.set_printoptions(linewidth=1000)
BACKGROUND:
I am having issues trying to search through some CSV files.
I've gone through the python documentation: http://docs.python.org/2/library/csv.html
about the csv.DictReader(csvfile, fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds) object of the csv module.
My understanding is that the csv.DictReader assumes the first line/row of the file are the fieldnames, however, my csv dictionary file simply starts with "key","value" and goes on for atleast 500,000 lines.
My program will ask the user for the title (thus the key) they are looking for, and present the value (which is the 2nd column) to the screen using the print function. My problem is how to use the csv.dictreader to search for a specific key, and print its value.
Sample Data:
Below is an example of the csv file and its contents...
"Mamer","285713:13"
"Champhol","461034:2"
"Station Palais","972811:0"
So if i want to find "Station Palais" (input), my output will be 972811:0. I am able to manipulate the string and create the overall program, I just need help with the csv.dictreader.I appreciate any assistance.
EDITED PART:
import csv
def main():
with open('anchor_summary2.csv', 'rb') as file_data:
list_of_stuff = []
reader = csv.DictReader(file_data, ("title", "value"))
for i in reader:
list_of_stuff.append(i)
print list_of_stuff
main()
The documentation you linked to provides half the answer:
class csv.DictReader(csvfile, fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds)
[...] maps the information read into a dict whose keys are given by the optional fieldnames parameter. If the fieldnames parameter is omitted, the values in the first row of the csvfile will be used as the fieldnames.
It would seem that if the fieldnames parameter is passed, the given file will not have its first record interpreted as headers (the parameter will be used instead).
# file_data is the text of the file, not the filename
reader = csv.DictReader(file_data, ("title", "value"))
for i in reader:
list_of_stuff.append(i)
which will (apparently; I've been having trouble with it) produce the following data structure:
[{"title": "Mamer", "value": "285713:13"},
{"title": "Champhol", "value": "461034:2"},
{"title": "Station Palais", "value": "972811:0"}]
which may need to be further massaged into a title-to-value mapping by something like this:
data = {}
for i in list_of_stuff:
data[i["title"]] = i["value"]
Now just use the keys and values of data to complete your task.
And here it is as a dictionary comprehension:
data = {row["title"]: row["value"] for row in csv.DictReader(file_data, ("title", "value"))}
The currently accepted answer is fine, but there's a slightly more direct way of getting at the data. The dict() constructor in Python can take any iterable.
In addition, your code might have issues on Python 3, because Python 3's csv module expects the file to be opened in text mode, not binary mode. You can make your code compatible with 2 and 3 by using io.open instead of open.
import csv
import io
with io.open('anchor_summary2.csv', 'r', newline='', encoding='utf-8') as f:
data = dict(csv.reader(f))
print(data['Champhol'])
As a warning, if your csv file has two rows with the same value in the first column, the later value will overwrite the earlier value. (This is also true of the other posted solution.)
If your program really is only supposed to print the result, there's really no reason to build a keyed dictionary.
import csv
import io
# Python 2/3 compat
try:
input = raw_input
except NameError:
pass
def main():
# Case-insensitive & leading/trailing whitespace insensitive
user_city = input('Enter a city: ').strip().lower()
with io.open('anchor_summary2.csv', 'r', newline='', encoding='utf-8') as f:
for city, value in csv.reader(f):
if user_city == city.lower():
print(value)
break
else:
print("City not found.")
if __name __ == '__main__':
main()
The advantage of this technique is that the csv isn't loaded into memory and the data is only iterated over once. I also added a little code the calls lower on both the keys to make the match case-insensitive. Another advantage is if the city the user requests is near the top of the file, it returns almost immediately and stops looking through the file.
With all that said, if searching performance is your primary consideration, you should consider storing the data in a database.
I'm using wget to fetch several dozen JSON files on a daily basis that go like this:
{
"results": [
{
"id": "ABC789",
"title": "Apple",
},
{
"id": "XYZ123",
"title": "Orange",
}]
}
My goal is to find row's position on each JSON file given a value or set of values (i.e. "In which row XYZ123 is located?"). In previous example ABC789 is in row 1, XYZ123 in row 2 and so on.
As for now I use Google Regine to "quickly" visualize (using the Text Filter option) where the XYZ123 is standing (row 2).
But since it takes a while to do this manually for each file I was wondering if there is a quick and efficient way in one go.
What can I do and how can I fetch and do the request? Thanks in advance! FoF0
In python:
import json
#assume json_string = your loaded data
data = json.loads(json_string)
mapped_vals = []
for ent in data:
mapped_vals.append(ent['id'])
The order of items in the list will be indexed according to the json data, since the list is a sequenced collection.
In PHP:
$data = json_decode($json_string);
$output = array();
foreach($data as $values){
$output[] = $values->id;
}
Again, the ordered nature of PHP arrays ensure that the output will be ordered as-is with regard to indexes.
Either example could be modified to use a mapped dictionary (python) or an associative array (php) if needs demand.
You could adapt these to functions that take the id value as an argument, track how far they are into the array, and when found, break out and return the current index.
Wow. I posted the original question 10 months ago when I knew nothing about Python nor computer programming whatsoever!
Answer
But I learned basic Python last December and came up with a solution for not only get the rank order but to insert the results into a MySQL database:
import urllib.request
import json
# Make connection and get the content
response = urllib.request.urlopen(http://whatever.com/search?=ids=1212,125,54,454)
content = response.read()
# Decode Json search results to type dict
json_search = json.loads(content.decode("utf8"))
# Get 'results' key-value pairs to a list
search_data_all = []
for i in json_search['results']:
search_data_all.append(i)
# Prepare MySQL list with ranking order for each id item
ranks_list_to_mysql = []
for i in range(len(search_data_all)):
d = {}
d['id'] = search_data_all[i]['id']
d['rank'] = i + 1
ranks_list_to_mysql.append(d)