Pandas dataframe only writing last row to .csv

Question

I would like to write these data frames to a csv file, however I am only writing the last row. The objective of my code is to call an API and get the highest temperature for "yesterday" for a given lat/lng.

My current output is:

I would like for my output to be:

Code:

import pandas as pd
import requests
import csv
import json
from datetime import datetime, timedelta
from pandas import DataFrame

#read csv

output_high_csv = r"C:\wab\outputempbeets1.csv"

se_ = requests.Session()

df = pd.read_csv(csvdata)
df = df [['lat', 'lon', 'field id']]

#convert Pandas series to string
dfText = df.astype(basestring)

#get lat/lng from dataframe
dfLat = dfText['lat']
dfLon = dfText['lon']
dfFid = dfText['field id']

#get values from series
latval = list(dfLat.values)
lonval = list(dfLon.values)
idVal = list(dfFid.values)
dayVal = datetime.strftime(datetime.now() - timedelta(1), '%Y-%m-%d')

#Zip Field ID, Lat, Lng

for latrow, lonrow, idVal in zip(latval, lonval, idVal):
    #send lat/lngs to DTN
    url = 'https://insight.api.wdtinc.com/daily-high-temperature/' + str(latrow )+'/' + str(lonrow) +'?start='+ dayVal +'T00:00:00Z&end=' +dayVal+'T01:00:00Z'+ '&unit=fahrenheit'
    r = se_.get(url, auth=('USERNAME', 'PASSWORD'), timeout= 10)
    # print(r.url)
    hiTemp = (json.loads(r.content)['series'][0]['value'])
    strTemp = str(hiTemp)
    tempDF = {'field id': [idVal],
        'high temperature': [strTemp]
        }
    df = DataFrame(tempDF,columns= ['field id', 'high temperature'])    
    dfList = [df]
    dfs = [df.set_index('field id') for df in dfList]
    i = pd.concat(dfs, axis=1)
    print i
    i.to_csv(output_high_csv, encoding='utf-8', index=True)`

When I print i my output is:

EDIT: When I use mode= 'a' Here is my output:

When mode a is used.

Answer 1

使用添加模式尝试一下：

i.to_csv(output_high_csv, encoding='utf-8', index=True, mode='a')

Answer 2

Your code is very convoluted. I think this is a simplified version of what you're attempting. It may have mistakes but if this doesn't answer your question, try and use it to simplify the code in your question.

import pandas as pd
import requests
import csv
import json
from datetime import datetime, timedelta
from pandas import DataFrame
from pathlib import Path

DATA_PATH = Path('C:/wab')
input_csv = 'my_data.csv'
output_csv = 'outputempbeets1.csv'

se_ = requests.Session()

df = pd.read_csv(DATA_PATH / input_csv,
                 usecols=['lat', 'lon', 'field id'],
                 dtype=str)

dayVal = datetime.strftime(datetime.now() - timedelta(1), '%Y-%m-%d')
dfs = []

def get_high_temp(lat, lon, dayVal):
    url = f'https://insight.api.wdtinc.com/daily-high-temperature/{lat}/{lon}'
    params = {
        'start': f'{dayVal}T00:00:00Z',
        'end': f'{dayVal}T01:00:00Z',
        'unit': 'fahrenheit',
    }
    response = se_.get(url, 
                       params=params, 
                       auth=('USERNAME', 'PASSWORD'),
                       timeout=10)

    hi_temp = str(json.loads(response.content)['series'][0]['value'])
    return hi_temp

for _, lat, lon, id_ in df.itertuples():
    hi_temp = get_high_temp(lat, lon, dayVal)
    temp_df = pd.DataFrame({'high temperature': [hi_temp],},
                           index=[id_])    
    dfs = dfs.append(temp_df)

pd.concat(dfs).to_csv(DATA_PATH / output_csv, encoding='utf-8')